The advances in imaging and semiconductor technology coupled with high-speed wireless transmissions are enabling multiview acquisition using camera arrays. However, the biggest challenge with a multiview system (a system where multiple cameras monitor the same scene from different viewing positions) is handling huge amount of data obtained from the multiple cameras, compressing them, and either storing or transmitting, and yet being low cost by not demanding too much computing power, energy and memory requirements. One of the main challenges with existing multiview coding (MVC) standard is the requirement of inter-camera communications for exploiting inter-view redundancies. This significantly increases encoder complexity, encoding delay, memory requirements and power at the encoders. Further, MVC requires encoding all video frames and therefore, requires more bit-rates or transmission bandwidth and drastically increases encoding complexity.
The distributed video coding (DVC) which was originally intended for monoview applications has been extended to multiview applications. The monoview DVC works on encoding only a few selected frames at an encoder of a transmitter and by using interpolation or extrapolation techniques at the decoder of a receiver to restore remaining frames. Therefore, some of the DVC concepts have been applied to MVC, as DVC is designed to achieve low complexity encoder and to address the drawbacks of MVC. The key objective of multiview distributed video coding (MDVC) is to efficiently encode different video streams at the transmitter, by exploiting the possible redundancies at the decoder of the receiver, thus obtaining benefits inherent to DVC, such as lower encoding complexity and embedded error resilience without needing intercommunication between different cameras. The MDVC achieves these objectives by encoding only few key video frames using standard predictive coding methods at the transmitter and sending to the decoder of the receiver and by sending only a few optimal number of syndrome bits of non-key video frames to the decoder of the receiver. In addition, the non-key video frame syndrome bits received are used for correcting errors of interpolated or extrapolated non-key video frames using the key video frames at the decoder of the receiver.
One of the key challenges of MDVC is optimal rate at which the syndrome bits need to be sent from the encoder of the transmitter to the decoder of the receiver for non-key video frames to achieve a required quality level. In existing DVC techniques, typically, a feedback channel is deployed through which the decoder of the receiver does rate control, which can be impractical in systems without feedback channel. Also, in other existing techniques, encoder/transmitter based rate estimation is deployed, which estimates syndrome bit rate using low-complex rate-estimation techniques. These low-complex rate-estimation techniques at the encoder of the transmitter may result in inaccuracies especially with fast moving video sequences and may lead to very low quality decoded video. In addition, these low-complex rate-estimation techniques may have to be applied in parallel to every non-key video frame, which may significantly increase overall encoder/transmitter complexity.